Linked data for beginners

Your library has great things—collections of materials and resources your patrons want; programs for children, teens and adults. Your successes are reflected in your circulation statistics, door counts and number of program attendees.

What if you could boost these efforts? Increase your library's visibility for patrons who find their information by searching on the web?

Linked data offers a way to do that.

The great stuff mentioned above? That stuff rarely appears in web search results.

Linked Library Service overcomes the problem of no library presence on the web by transforming robust MARC records into machine-optimized formats the web understands. This data is published to the Library.Link network. The result: relevance, what library users (and non-library users) want at their point of need, when they *do* the searching.

Consider the recent Pokemon Go craze. What if someone searching the web for a Snorlax stumbled upon the Pokemon books available at your library? What if this person didn't have a library card and found out how easy it is to get one? What if this person checked out all of your library's Pokemon books? Your library just became relevant to this user, now a patron, because your data was on the web. Linked data made sure your library benefitted from this organic searching.

From there, the possibilities are exponential. Have you typed "movies" into a Google search? You get a list of movies playing near you. This direct searching is from linked data being pulled to create knowledge boxes. Your data can fuel this kind of trusted, reliable information for your patrons.

You can further enrich this linked data with NoveList Select for Linked Data, allowing potential patrons who are searching the web to find that not only do you have the books they're looking for, but you also offer suggestions for more like them, more authors to read, and to discover what appeals to them about the books that truly matter. NoveList enrichment creates more access points, more relationships, more links, and more data for algorithms to understand and respond to. The machine friendly side of the data is richer, while the human friendly side looks nicer.